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- W2982160553 abstract "Standard methods for meta-analysis are limited to pooling tasks in which a single effect size is estimated from a set of independent studies. However, this setting can be too restrictive for modern meta-analytical applications. In this contribution, we illustrate a general framework for meta-analysis based on linear mixed-effects models, where potentially complex patterns of effect sizes are modeled through an extended and flexible structure of fixed and random terms. This definition includes, as special cases, a variety of meta-analytical models that have been separately proposed in the literature, such as multivariate, network, multilevel, dose-response, and longitudinal meta-analysis and meta-regression. The availability of a unified framework for meta-analysis, complemented with the implementation in a freely available and fully documented software, will provide researchers with a flexible tool for addressing nonstandard pooling problems." @default.
- W2982160553 created "2019-11-01" @default.
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- W2982160553 date "2019-10-24" @default.
- W2982160553 modified "2023-10-15" @default.
- W2982160553 title "An extended mixed‐effects framework for meta‐analysis" @default.
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- W2982160553 doi "https://doi.org/10.1002/sim.8362" @default.
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